Document Type : Research Paper

Authors

1 Department of Civil Engineering, Tafresh University, Tafresh 39518 79611, ‎Iran

2 UQAT-Polytechnique Research Institute on Mine and Environment (RIME), QC, Canada

Abstract

Accurate modeling of the drainage basin, including its spatial and temporal distribution of hydrological parameters and rainfall-runoff process, is very important in many applications. As an example, design flood estimation in hydraulic structures, which has the main role in the construction cost, is a result of rainfall-runoff simulation. The Rudbar Lorestan dam project is a part of the hydroelectric development projects complex in the Dez River basin. This project is located in a mountainous zone 200 Km away from Isfahan on the Rudbar River and 100 Km away from the south of Aligudarz. The aim of the Rudbar Dam and power plant project was to use the hydroelectric potential that is caused by the different elevations between the dam position and the power plant location. Due to the About 300 Meters difference in elevation from the dam axis to the power plant location set as one of Iran's prominent hydroelectricity projects. There are many consulting engineers in these projects, previous studies, and their main study result (flood design) shows a 17% difference from each other. due to the significant mentioned difference caused by using experimental methods and personal judgment, an effort was made in this research to simulate a large part of the Rainfall-Runoff process and model the water movement current on the basin surface with WMS software, and by taking the results of previous studies, the results of executing point of view and theory point of view had been compared. For this purpose, two internal and external representative basins were simulated, and the results were compared to evaluate the ability of the model. Simulating the main basin refuses the older studies by the difference near 20%, and confirms the newer studies by a difference of about 10%.

Keywords

Main Subjects

Beck, M. B., Kleissen, F. M., & Wheater, H. S. (1990). Identifying flow paths in models of surface water acidification. Reviews of Geophysics28(2), 207-229. doi: 10.1029/RG028i002p00207.
Clark, C. O. (1945). Storage and the unit hydrograph. Transactions of the American Society of Civil Engineers110(1), 1419-1446. doi: 10.1061/taceat.0005800.
Crawford, N. H., & Linsley, R. K. (1966). Digital Simulation in Hydrology'Stanford Watershed Model 4.
Farahani, S. V., Hejazi, S. M., & Boroomand, M. R. (2021). Torsional Alfvén wave cascade and shocks evolving in solar jets. The Astrophysical Journal906(2), 70. doi: 10.3847/1538-4357/abca8
Freeze, R. A., & Harlan, R. L. (1969). Blueprint for a physically-based, digitally-simulated hydrologic response model. Journal of hydrology9(3), 237-258. doi: 10.1016/0022-1694(69)90020-1.
Hromadka, T. V., & Whitley, R. J. (1994). The rational method for peak flow rate estimation 1. JAWRA Journal of the American Water Resources Association30(6), 1001-1009. doi: 10.1111/j.1752-1688.1994.tb03348.x.
Kokkonen, T. S., & Jakeman, A. J. (2001). A comparison of metric and conceptual approaches in rainfall‐runoff modeling and its implications. Water Resources Research37(9), 2345-2352. doi: 10.1029/2001WR000299.
Vidyarthi, V. K., & Jain, A. (2023). Development of simple semi-distributed approaches for modelling complex rainfall–runoff process. Hydrological Sciences Journal, 1-18. doi: 10.1080/02626667.2023.2197117.
Lee, K. K. F., Ling, L., & Yusop, Z. (2023). The Revised Curve Number Rainfall–Runoff Methodology for an Improved Runoff Prediction. Water15(3), 491.
Milly, P. C. D., & Eagleson, P. S. (1988). Effect of storm scale on surface runoff volume. Water Resources Research24(4), 620-624. doi: 10.1029/WR024i004p00620.
Namin, M. M., & Boroomand, M. R. (2012). A time splitting algorithm for numerical solution of Richard’s equation. Journal of Hydrology444, 10-21. doi: 10.1016/j.jhydrol.2012.03.029
Mulvaney, T. J. (1851). On the use of self-registering rain and flood gauges in making observations of the relations of rainfall and flood discharges in a given catchment. Proceedings of the institution of Civil Engineers of Ireland4(2), 18-33.
Rezaie-Balf, M., Zahmatkesh, Z., & Kim, S. (2017). Soft computing techniques for rainfall-runoff simulation: local non–parametric paradigm vs. model classification methods. Water Resources Management31, 3843-3865. doi: 10.1007/S11269-017-1711-9.
Shah, S. M. S., O'connell, P. E., & Hosking, J. R. M. (1996). Modelling the effects of spatial variability in rainfall on catchment response. 2. Experiments with distributed and lumped models. Journal of Hydrology175(1-4), 89-111. doi: 10.1016/S0022-1694(96)80007-2.
Sherman, L. K. (1932). Streamflow from rainfall by the unit-graph method. Eng. News Record108, 501-505. http://ci.nii.ac.jp/naid/10023998652/en/
Singh, V. P. (Ed.). (1995). Computer models of watershed hydrology (Vol. 1130). Highlands Ranch, CO: Water resources publications.
Stephenson, G. R., & Freeze, R. A. (1974). Mathematical simulation of subsurface flow contributions to snowmelt runoff, Reynolds Creek Watershed, Idaho. Water Resources Research10(2), 284-294. doi: 10.1029/WR010i002p00284.
Strapazan, C., Irimuș, I. A., Șerban, G., Man, T. C., & Sassebes, L. (2023). Determination of Runoff Curve Numbers for the Growing Season Based on the Rainfall–Runoff Relationship from Small Watersheds in the Middle Mountainous Area of Romania. Water15(8), 1452. doi: 10.3390/W15081452.